From 22ad2e326a27b8916542d504ca1a855c26b5b9ec Mon Sep 17 00:00:00 2001 From: Kylli Ek Date: Thu, 5 Sep 2024 14:26:48 +0300 Subject: [PATCH] Update parallel.md --- materials/parallel.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/materials/parallel.md b/materials/parallel.md index 7a9b5ada..5f085260 100644 --- a/materials/parallel.md +++ b/materials/parallel.md @@ -68,8 +68,6 @@ Many programming languages have packages for parallel computing. * [Julia multi-threading](https://docs.julialang.org/en/v1/manual/multi-threading/#man-multithreading) * [MATLAB Parallel Computing Toolbox](https://se.mathworks.com/products/parallel-computing.html) -If you have for-loops, `map()/*apply()`-functions or similar in your scripts, it can be rather easy to make the script run in parallel. - ## External tools to run the scripts in parallel The external tools enable running the scripts in parallel. This way of running programs is also called task farming or high throughput computing. The tools have different complexity and different features. The simpler of these tools are for running same script with different input paramaters, for example different input files, scenarios, time frames etc. More complicated tools support managing the whole workflow with several steps and with dependecies between steps. Workflow tools also help with making your work more reproducible by recording the computational steps and data. See [CSC Docs: High-throughput computing and workflows](https://docs.csc.fi/computing/running/throughput/) for more information.